Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations and no output schema, the description carries the full burden and does well: it discloses the returned quantities (quartile distances, radius, survival percentages at 7/30/61 days/1 year with citations), that findings carry provenance tags (studied / not studied), and the key behavioral rule that only 'life' changes the distance. It omits auth/rate-limit and error behavior, which is minor for a read-only lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded in the first clause, but the body is a single dense run-on block mixing return values, parameter effects, citations, and a URL, making it hard to scan. Every sentence has content, but the lack of breaks or ordering hurts readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 14-parameter, no-annotation, no-output-schema tool, the description covers purpose, return contents, parameter-to-output effects, and source attribution, which is enough for correct invocation. Minor gaps (pagination/format of the returned structure) are acceptable given no output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so a baseline of 3 applies, but the description adds real meaning beyond the schema: it groups which parameters affect the output (life drives distance; sex/neuter/age/breed/curiosity/area/rain drive the search-order steps and per-item findings). This tells an agent how inputs map to output dimensions, which the flat enum descriptions do not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Names a specific verb+resource: it returns, for a lost cat, the distance distribution from where it fled to where it was found, search-radius guidance, first places to search, and survival-rate-by-days, all sourced to Huang et al. 2018. An agent can tell exactly what the tool produces and that it is distinct from the finance/price siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes three example queries ("猫が逃げた どこを探す", "猫 脱走 帰ってくる確率", "猫 帰ってこない 何日") to this tool, giving clear when-to-use context. No when-not or alternative tool is named, but no sibling overlaps this domain, so the guidance is effectively sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.